Surendran Praveen, Stewart Isobel D, Au Yeung Victoria P W, Pietzner Maik, Raffler Johannes, Wörheide Maria A, Li Chen, Smith Rebecca F, Wittemans Laura B L, Bomba Lorenzo, Menni Cristina, Zierer Jonas, Rossi Niccolò, Sheridan Patricia A, Watkins Nicholas A, Mangino Massimo, Hysi Pirro G, Di Angelantonio Emanuele, Falchi Mario, Spector Tim D, Soranzo Nicole, Michelotti Gregory A, Arlt Wiebke, Lotta Luca A, Denaxas Spiros, Hemingway Harry, Gamazon Eric R, Howson Joanna M M, Wood Angela M, Danesh John, Wareham Nicholas J, Kastenmüller Gabi, Fauman Eric B, Suhre Karsten, Butterworth Adam S, Langenberg Claudia
British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
British Heart Foundation Centre of Research Excellence, School of Clinical Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK.
Nat Med. 2022 Nov;28(11):2321-2332. doi: 10.1038/s41591-022-02046-0. Epub 2022 Nov 10.
Garrod's concept of 'chemical individuality' has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P < 1.25 × 10) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships.
加罗德的“化学个体性”概念有助于理解人类疾病的分子起源。非靶向高通量代谢组学技术可大规模深入呈现人类代谢的全貌。我们利用在19994名个体中检测的913种代谢物研究了人类血浆代谢组的遗传结构，在330个基因组区域内鉴定出2599个变异 - 代谢物关联（P < 1.25×10），其中罕见变异（次要等位基因频率≤1%）解释了9.4%的关联。通过对每个区域的代谢物进行联合建模，我们识别出423个区域共调控的变异 - 代谢物簇，称为遗传影响代谢型。我们为62.4%的这些遗传影响代谢型确定了因果基因，为基础代谢物生理学和临床相关性提供了新见解，包括通过代谢物指导发现潜在的药物不良反应（如DPYD和SRD5A2）。我们发现代谢性先天性疾病致病基因有强烈富集，非致病性变异携带者的代谢物关联和临床表型实例与代谢性先天性疾病特征相符。对代谢物特异性遗传评分进行系统的表型随访揭示了多种潜在的病因关系。
